Update app.py

app.py

@@ -1,119 +1,80 @@
-# Autors: [Escriu aquí el teu nom] i [nom del company si en teniu]
-# Pràctica 26/05/2025 - Agent amb eines noves: traductor i resumidor
-
-# 1. Instal·lació automàtica de llibreries (al principi del fitxer)
-import subprocess
-import sys
-
-def install(package):
-    subprocess.check_call([sys.executable, "-m", "pip", "install", package])
-
-# Instalar primero las dependencias pesadas
-install("torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu")
-install("transformers")
-install("deep-translator")
-install("langchain")
-install("sentencepiece")
-
-# 2. Importaciones después de las instalaciones
-from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
+from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
 import datetime
 import requests
 import pytz
 import yaml
 from tools.final_answer import FinalAnswerTool
-from Gradio_UI import GradioUI
-from langchain.tools import Tool
-
-# 3. Configuración del traductor (no requiere PyTorch/TensorFlow)
-from deep_translator import GoogleTranslator
 
-def translate_text(text: str) -> str:
-    """Traduce texto a inglés usando Google Translate"""
-    try:
-        return GoogleTranslator(source='auto', target='en').translate(text)
-    except Exception as e:
-        return f"Error en traducción: {str(e)}"
-
-translate_tool = Tool(
-    name="TextTranslator",
-    func=translate_text,
-    description="Translate input text to English. Input can be in any language."
-)
-
-# 4. Configuración alternativa del resumidor (sin PyTorch/TensorFlow)
-from transformers import pipeline
-
-try:
-    # Intentamos cargar un modelo pequeño que pueda funcionar sin GPU
-    summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
-except:
-    # Fallback a una implementación más simple si falla
-    def simple_summarizer(text: str) -> str:
-        """Resumen básico tomando las primeras oraciones"""
-        sentences = text.split('.')
-        return '. '.join(sentences[:3]) + '.' if len(sentences) > 3 else text
-    
-    summarizer = simple_summarizer
-
-def summarize_text(text: str) -> str:
-    try:
-        if callable(summarizer):
-            summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
-            return summary[0]['summary_text'] if isinstance(summary, list) else summary
-        return summarizer(text)
-    except Exception as e:
-        return f"Error en resumen: {str(e)}"
+from Gradio_UI import GradioUI
 
-summarize_tool = Tool(
-    name="TextSummarizer",
-    func=summarize_text,
-    description="Summarize input text. Use it for long paragraphs or documents."
-)
+# Below is an example of a tool that does nothing. Amaze us with your creativity !
+@tool
+def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
+    #Keep this format for the description / args / args description but feel free to modify the tool
+    """A tool that does nothing yet 
+    Args:
+        arg1: the first argument
+        arg2: the second argument
+    """
+    return "What magic will you build ?"
 
-# 5. Herramientas adicionales
 @tool
 def get_current_time_in_timezone(timezone: str) -> str:
-    """Obtiene la hora actual en una zona horaria específica"""
+    """A tool that fetches the current local time in a specified timezone.
+    Args:
+        timezone: A string representing a valid timezone (e.g., 'America/New_York').
+    """
     try:
+        # Create timezone object
         tz = pytz.timezone(timezone)
+        # Get current time in that timezone
         local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
         return f"The current local time in {timezone} is: {local_time}"
     except Exception as e:
-        return f"Error fetching time: {str(e)}"
+        return f"Error fetching time for timezone '{timezone}': {str(e)}"
+
+
+
 
-# 6. Configuración del agente
 final_answer = FinalAnswerTool()
 
+# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
+# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
+
+
 model = HfApiModel(
     max_tokens=2096,
     temperature=0.5,
-    model_id="mistralai/Mistral-Small-3.1-24B-Instruct-2503",
+    # The following two models were given originally but are giving Error
+    # model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
+    # model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud', 
+    # Mistral works well. but writes its own tools
+    model_id = "mistralai/Mistral-Small-3.1-24B-Instruct-2503",
+    # model_id = "mistralai/Mistral-Nemo-Instruct-2407",
+    # model_id = "microsoft/Phi-3-mini-4k-instruct",
     custom_role_conversions=None,
 )
 
-try:
-    image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
-except:
-    @tool
-    def image_generation_tool(prompt: str) -> str:
-        return "Image generation disabled in this environment"
 
-# 7. Carga de plantillas y creación del agente
+
+# Import tool from Hub
+image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
+
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
 
+
 agent = CodeAgent(
     model=model,
-    tools=[
-        translate_tool,
-        summarize_tool,
-        get_current_time_in_timezone,
-        image_generation_tool,
-        final_answer
-    ],
+    tools=[final_answer, image_generation_tool, get_current_time_in_timezone, my_custom_tool], ## add your tools here (don't remove final answer)
+    #tools=[final_answer, image_generation_tool, my_custom_tool, DuckDuckGoSearchTool()], ## add your tools here (don't remove final answer)
+    max_steps=6,
+    verbosity_level=1,
+    grammar=None,
+    planning_interval=None,
+    name=None,
+    description=None,
     prompt_templates=prompt_templates
 )
 
-# 8. Iniciar la interfaz
 GradioUI(agent).launch()